Finally, A Modern Big Data Business Intelligence Platform

“As the complexity and volume of data increase, self-service solutions need to evolve to accommodate both. (…) AtScale sits between the BI user and Big Data.”

– Jessica Davis, InformationWeek

Big Data Business Intelligence: Modernize BI for Your Data.

The average BI tool is 22 years old. Don’t expect any of them to work natively with Big Data. Add AtScale to add speed, scale and security across all of your Big Data assets. Hadoop. Non-Hadoop. On-Premises. In the Cloud.

Speed, Scale and Simplicity

Speed: Blazing-Fast Response Time on Big Data
You might have deployed Hadoop alongside your Teradata, Netezza or Vertica. Regardless if you’ve deployed it on Cloudera, Hortonworks or MapR, your Hadoop cluster won’t natively perform at the same speed as standard MPP platforms. Until you add AtScale. Customers experience at least a 100X performance boost when they use our software. Find out more here.

Scale and Consistency: One Version of the Truth
Managing multiple data assets means that your team has to maintain multiple definitions, calculations, dimensions and metrics….in multiple places! AtScale is the industry’s only business semantic software that brings metadata uniformity and consistency across your data portfolio, on-premises, in the cloud, in Hadoop or not.

Simplicity: It Just Works
Managing Big Data in the Enterprise is hard. Teradata is different from Hadoop. Hadoop is different from Google BigQuery. BigQuery is different from RedShift. Yet, your business requires that it all just works. In order to “just make it work”, you need superior architecture. And that’s what AtScale’s brings to the table. AtScale offers Big Data Business Intelligence as a service. With AtScale, you won’t need to move data. You won’t need to create physical definitions. You won’t have to install new client software or server daemons. It just works.

A Framework for
“Big Business Intelligence”

The New World of Big Data: Past, Present and Future
Every IT executive needs a strategy that transcends their past, present and future data investments. Teradata might not work like Hadoop. Hadoop might be different from BigQuery. It doesn’t mean you need to have a separate team for each though. With AtScale, you can unify your efforts and maximize your value across all data, for all users.

Load Once. Use Everywhere.
Doing BI on Big Data used to mean data ingestion, movement, preparation and presentation. How many copies of the same data would you need to manage and prepare if you had at least four types of data platforms? (non-Hadoop, Hadoop, On-Premises, Cloud). AtScale introduces a new way to think about secure and self-service access to your enterprise data.

A Modern Architecture for
Big Data

Bring Data Where Users Live
When considering a modern BI platform, enterprises should take an inventory of the various visualization tools they own. Most will find 10s, sometimes 100s. An IT strategy forces users to abandon their preferred tools (think Excel, Tableau or others) for the sake of supporting new data platforms like Hadoop or Google BigQuery is fraught with peril. The most successful enterprises bring data to the users and let them draw insights, from within the tools they already own, use and love.

Standardize Where It Matters
When considering standardization, enterprises have historically worked on large enterprise data warehouse (EDW) projects. Most take too long or fail, leaving the organization with a hodgepodge of data assets, each governed by siloed definitions and business models. This has created chaos and affected enterprises’ ability to work off consistent and well-understood business metrics. The most successful enterprises do not move data around. Rather, they use a Universal Semantic LayerTM like AtScale’s to define business logic centrally, regardless what BI tools people use, regardless of whether the data is on Hadoop, not-on Hadoop, on-premises and in the Cloud.

Leverage Open Source
When it comes to insights for employees, speed matters: any query returning in more than 60 seconds is not interactive. Customers that are struggling with speed often do so because they’ve been on proprietary engines or antiquated approaches such as data marts, extracts or exports. Over the last 6 months, most SQL-on-Big-Data engines have more than doubled their speed. In other words, modern BI platforms that leverage open-source have experienced performance benefits faster than any proprietary effort.